Users have become accustomed to interacting with devices such as smart phones and tablet computers using personal digital assistant applications. Typically, users speak or type a question to their device e.g., to do a web search, and the personal digital assistant application associated with their device attempts to answer the question by searching the Internet, or by searching a calendar or contacts associated with the user of the device.
While such personal digital assistant applications are useful, they fail to take advantage of the wealth of data available to modern devices. For example, modern devices often include numerous sensors such as cameras, microphones, global positioning systems, accelerometers, barometers, etc. In addition, device users may be associated with additional devices such as fitness trackers, smart watches, home security systems, smart televisions, video game consoles, etc., and each device may be associated with its own set of sensors.
While the sensor data provided from the numerous sensors is capable of providing valuable information and insights to the user, there is currently no way for the user to search, integrate, or analyze this data using the personal digital assistant applications that they are familiar with.
Further, the current digital assistant applications are primarily reactive in nature. While users can set up alarms or reminders based on temporal events, these applications wait for the user to initiate a command/query and thus they do not proactively perform any actions.